Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement
Alternative ways of conducting inference and measurement for long-horizon forecasting are explored with an application to dividend yields as predictors of stock returns. Monte Carlo analysis indicates that the L. Hansen and R. Hodrick (1980) procedure is biased at long horizons, but the alternatives perform better. These include an estimator derived under the null hypothesis as in M. Richardson and T. Smith (1991), a reformulation of the regression as in N. Jegadeesh (1990), and a vector autoregression (VAR) as in J. Campbell and R. Shiller (1988), S. Kandel and R. Stambaugh (1988), and J. Campbell (1991). The statistical properties of long-horizon statistics generated from the VAR indicate interesting patterns in expected stock returns. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 5 (1992)
Issue (Month): 3 ()
|Contact details of provider:|| Postal: Oxford University Press, Journals Department, 2001 Evans Road, Cary, NC 27513 USA.|
Web page: http://www.rfs.oupjournals.org/
More information through EDIRC
|Order Information:||Web: http://www4.oup.co.uk/revfin/subinfo/|
When requesting a correction, please mention this item's handle: RePEc:oup:rfinst:v:5:y:1992:i:3:p:357-86. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Oxford University Press)or (Christopher F. Baum)
If references are entirely missing, you can add them using this form.